The subject matter of this specification can be embodied in, among other things, a method that includes receiving an audio signal and initiating speech recognition tasks by a plurality of speech recognition systems (SRS's). Each SRS is configured to generate a recognition result specifying possible speech included in the audio signal and a confidence value indicating a confidence in a correctness of the speech result. The method also includes completing a portion of the speech recognition tasks including generating one or more recognition results and one or more confidence values for the one or more recognition results, determining whether the one or more confidence values meets a confidence threshold, aborting a remaining portion of the speech recognition tasks for SRS's that have not generated a recognition result, and outputting a final recognition result based on at least one of the generated one or more speech results.
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2. The computer-implemented method of claim 1, wherein each of the plurality of same particular speech recognition results is obtained from a different one of the subset of the SRSs.
3. The computer-implemented method of claim 1, wherein a combination of the confidence values is further weighted based on a distribution of the confidence values obtained from the subset of the SRSs that generated the plurality of same particular speech recognition results.
4. The computer-implemented method of claim 1, wherein a combination of the confidence values is further weighted based on one or more characteristics of the subset of the SRSs that generated the plurality of same particular speech recognition results.
5. The computer-implemented method of claim 4, wherein the one or more characteristics include one or more characteristics selected from a group consisting of one or more overall levels of accuracy for a respective SRS of the subset of the SRSs that generated the plurality of same particular speech recognition results, one or more contextual levels of accuracy within a context for the audio signal for the respective SRS, and one or more temporal levels of accuracy for one or more periods of time for the respective SRS.
6. The computer-implemented method of claim 1, wherein a combination of the confidence values is further weighted based on a level of similarity between respective SRSs of the subset of the SRSs that generated the plurality of same particular speech recognition results.
7. The computer-implemented method of claim 1, wherein a combination of the confidence values is further weighted based on error rates of the subset of the SRSs that generated the plurality of same particular speech recognition results.
9. The device of claim 8, wherein each of the plurality of same particular speech recognition result is obtained from a different one of the subset of the SRSs.
10. The device of claim 8, wherein a combination of the confidence values is further weighted based on one or more characteristics of the subset of the SRSs that generated the plurality of same particular speech recognition results.
11. The device of claim 8, wherein a combination of the confidence values is further weighted based on a level of similarity between respective SRSs of the subset of the SRSs that generated the plurality of same particular speech recognition results.
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May 27, 2020
December 13, 2022
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